Buckets:
文本引导的深度图到图像生成
StableDiffusionDepth2ImgPipeline 允许你传入文本提示词和初始图像,以作为生成新图像的条件。此外,你还可以传入 depth_map 来保留图像结构。如果未提供 depth_map,该流水线会通过集成的 深度估计模型 自动预测深度。
首先,创建一个 StableDiffusionDepth2ImgPipeline 的实例:
import torch
from diffusers import StableDiffusionDepth2ImgPipeline
from diffusers.utils import load_image, make_image_grid
pipeline = StableDiffusionDepth2ImgPipeline.from_pretrained(
"stabilityai/stable-diffusion-2-depth",
dtype=torch.float16,
use_safetensors=True,
).to("cuda") # or "mps", "xpu", "cpu"
现在将您的提示词传递给 pipeline。您还可以传入 negative_prompt,以防止某些词语影响图像的生成方式:
url = "http://images.cocodataset.org/val2017/000000039769.jpg"
init_image = load_image(url)
prompt = "two tigers"
negative_prompt = "bad, deformed, ugly, bad anatomy"
image = pipeline(prompt=prompt, image=init_image, negative_prompt=negative_prompt, strength=0.7).images[0]
make_image_grid([init_image, image], rows=1, cols=2)
| 输入 | 输出 |
|---|---|
Xet Storage Details
- Size:
- 1.92 kB
- Xet hash:
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